Shuang Sha

With the rise of AI, can technical writing naturally achieve 10x or even 100x efficiency gains? The answer is no—multiple challenges still constrain the effective use of AI. Today, technical documentation management in large enterprises commonly faces three major pain points: misalignment between R&D and documentation leading to version chaos, where operations teams often use old manuals to operate new equipment; static documents that fail to meet the needs of different roles, resulting in low information retrieval efficiency; and high collaboration costs across the full lifecycle, with repetitive work accounting for over 60%, trapping technical writers in low-efficiency internal competition.

Based on real-world projects, this session presents a human–AI collaborative practice that builds a documentation development model centered on intelligent information blocks. The approach achieves a 60% reduction in business process complexity and supports a flatter organizational structure, offering a benchmark “living documentation” practice that intelligently bridges the gap from content to action.